Extracellular vesicles (EVs) are small, sub-micron membrane-bound particles that function in cell-to-cell communication and have potential to be used in diagnostics, therapy, and biological investigations. However, common characterization methods for EVs lack functional information and rely on “bulk” metrics that lack single-EV resolution. Recent work has applied label-free multimodal nonlinear optical microscopy for characterization of EVs via NAD(P)H and FAD autofluorescence. Here, we characterize EVs isolated from urine and serum from human breast cancer surgery patients and breast reduction surgery patients who have no history of breast cancer to examine altered cancer-related metabolic signatures in cancer-associated EVs.
Tumor-associated extracellular vesicles (TEVs), which represent a unique kind of inter-cellular communication carrier, have been found to play vital roles in directing the invasion and metastasis of tumor cells. However, because the human tumor microenvironment and TEVs significantly degrade or lose vitality over relatively brief periods of time after breast cancer surgical excision, lab-based studies with fresh human tissue specimens cannot provide accurate TEV information. By designing and building a portable label-free nonlinear imaging system, we have been able to conduct intraoperative imaging of fresh, unstained breast tissue specimens immediately after excision. Various features of the breast tumor microenvironment from multimodal nonlinear images were characterized to indicate tumor progression, invasiveness, and tumor grade, such as tumor-accommodating collagen structure visualized using second harmonic generation imaging, fibroblasts shown by two photon auto-fluorescence, and TEVs highlighted using third harmonic generation imaging. In particular, we found TEV count as a promising biomarker of tumor aggressiveness and margin distance. A decreasing trend of TEV counts with larger margin distance and lower cancer aggressiveness grades was revealed among 18 breast cancer cases. In addition, clear differences in TEV counts between images collected from breast cancer cases and healthy breast reduction cases, in another aspect, validate the potential of identifying TEVs using our imaging method. Acquisition and interpretation of these intraoperative image data not only provided assessment of the human tumor microenvironment, but also offered the potential to intraoperatively assess tumor margin distance and determine tumor aggressiveness.
Label-free multi-photon imaging has been a powerful tool for studying tissue microstructures and biochemical distributions, particularly for investigating tumors and their microenvironments. However, it remains challenging for traditional bench-top multi-photon microscope systems to conduct ex vivo tumor tissue imaging in the operating room due to their bulky setups and laser sources. In this study, we designed, built, and clinically demonstrated a portable multi-modal nonlinear label-free microscope system that combined four modalities, including two- and three- photon fluorescence for studying the distributions of FAD and NADH, and second and third harmonic generation, respectively, for collagen fiber structures and the distribution of micro-vesicles found in tumors and the microenvironment. Optical realignments and switching between modalities were motorized for more rapid and efficient imaging and for a light-tight enclosure, reducing ambient light noise to only 5% within the brightly lit operating room. Using up to 20 mW of laser power after a 20x objective, this system can acquire multi-modal sets of images over 600 μm × 600 μm at an acquisition rate of 60 seconds using galvo-mirror scanning. This portable microscope system was demonstrated in the operating room for imaging fresh, resected, unstained breast tissue specimens, and for assessing tumor margins and the tumor microenvironment. This real-time label-free nonlinear imaging system has the potential to uniquely characterize breast cancer margins and the microenvironment of tumors to intraoperatively identify structural, functional, and molecular changes that could indicate the aggressiveness of the tumor.
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